1) What do understand by the terms a) Empirical Formula b) isomerism and what conclusions can you draw from the following observations about the chemical nature of the organic liquid D?
a) D (relative molecular mass 72 ) has the following persentage composition by mass: Carbon 66.7, hydrogen 11.1, oxygen 22.2
b) D gives an orange precipitate with 2,4 dinitrophenyhydrazine reagent
c) D reacts with phosphorous pentachloride but no fumes of hydrogen are evolved
d) D gives a pale yellow precipitate in warming with iodine and aqueous sodium hydroxide
e) Write the full structural formula for a compound that conforms to all the above data explaining how you arrive to that answer?
* D undergoes catalytic reduction with hydrogen to give a liquid E which, on dehydration with concentrated sulfuric acid give a colorless gas F. Ozonolysis of F gives a single organic product G with molecular formula C2H4O. Identify E, F, and G and write equations for above reactions.
This in-depth solution contains step-by-step explanations and annotated diagrams to explain the concepts of empirical formula, isomerism, reaction mechanisms and also the qualitative observations of organic liquid D.
Descriptive statistics for cross-sectional data: term project
Deliverable 1: Descriptive Statistics
(10 points) Our main emphasis in the course is "inferential" statistics which means taking samples and drawing an inference or conclusions about the population.
Access raw data or a database from government, business, health, and similar official Web sites pertaining to your area of interest. Collect at least 30 pieces of numerical (quantitative) metric data (see p.15) but no more than an n of 50 (30-50 observations and only one theme). If you have a sample larger than 50 randomly select a subset so your n (sample size) is no more than 50. Explain where these data came from and why they are of interest to you.
Describe the population and the variable. From the data, plot a histogram, a stem-and-leaf diagram and an ogive (polygon). Also calculate the mean, median, mode, range, standard deviation, and quartiles of the data. Create a boxplot. Explain what this analysis tells you.
In a separate appendix (or spreadsheet), list all 30-50 observations labeled from 1 to 30 (up to 50 if n=50) so I can duplicate your work if necessary.
Since you will be doing a histogram you will need to select a sample that consists of numerical (quantitative) data not categorical (qualitative) data (see p.15). A bar graph is not the same as a histogram so in Excel, click bars (right click properties) /format data series/options/gap width (should equal to zero) and this should get rid of the gaps (histograms do not contain gaps...only bar graphs are used for categorical data. Your textbook describes other methods to provide an acceptable histogram and other graphics. If you have a category/class in the data with zero observations then try to get rid of the gap by extending the width of the class interval or at the very least explain it in your comments. Histograms and other descriptive statistics should not add to the confusion or generate more questions but should answer and explain the data. Look at your descriptive statistics and ask if there are any questions that would be asked and can you answer them by modifying the descriptive statistics or adding a comment or label. See also p. 81, exhibits 2.1 and 2.2.View Full Posting Details